The human retina is a thin layer of neural tissue at the back of the eye that transforms light into electrical signals which are sent to the brain. The retina can be divided into distinct regions related to their visual function. These regions include the macula (where the majority of photoreceptor cells responsible for high-acuity color vision lie) pericentral and peripheral retina (which includes everything outside the macula and is responsible for our peripheral vision). The retina peripheral to the macula includes a non-photosensitive structure known as the optic disc. Automatic optic disc detection in retinal images is an important task due to the optic disc's usefulness as a landmark for further retinal image processing along with the usefulness of its appearance as an indicator for some diseases of the eye. In the case of the former, establishing the optic disc as a landmark allows for the creation of a coordinate system that may be used to better assess the position of disease features or help one detect other anatomical structures of the retina, such as the fovea. The fovea is a region within the center of the macula that includes the vast majority of cone cells and is responsible for nearly all of our high acuity color vision. Because the macula is crucial for normal vision, it is important that eye care specialists be able to closely monitor structural changes in this region that can lead to irreparable cell death.
To visually observe and monitor the structure of the retina, physicians currently rely on various medical imaging techniques, one of which being fundus autofluorescence (AF) photography. The word fundus refers to the surface of an organ opposite its opening, and in this case refers to the retina. AF imaging relies on the inherent fluorescence of proteins and other molecules produced by cells in the retina, particularly lipofuscin. These molecules can be excited by striking them with light of certain wavelengths, causing the molecules to reflect light of a longer wavelength back to the camera. This reflected light can be captured and turned into an electrical signal to be processed and displayed as a monochromatic image of the retina. In such images areas exhibiting excessive accumulation of metabolic products such as lipofuscin appear brighter than surrounding tissue, and areas with decreased accumulation appear darker. Areas where cells have died completely in a process known as atrophy appear black. The observable image feature is known as geographic atrophy and may appear similar to the optic disc in AF images.
While methods for detecting the optic disc in color fundus images of the retina exist, there are currently none that address the challenges of detecting the optic disc in monochromatic AF images. Additionally, existing methods fail to address the challenges introduced by the optic disc being in the presence of geographic atrophy. For example, geographic atrophy may occur as a disease feature characteristic of dry Age Related Macular Degeneration (AMD), which afflicts millions of people. AMD is a disease that can be easily observed using AF imaging. Although not yet developed, automatic detection of the geographic atrophy present in AF images has the potential to allow physicians to easily monitor the growth of these regions of atrophy if they can be distinguished from optic discs. Therefore, the detection and exclusion of the optic disc from atrophy segmentation is desirable, but no methods currently exist to do so. In addition to differentiating the optic disc from atrophy or other similar regions in AF images, optic disc detection is also hampered by the narrow angle (e.g. 30°) field of view in AF images focused on the macula. Such narrow field of view frequently leaves the optic disc partially beyond the edge of the image, thereby limiting use of geometric or template-matching approaches.
Moreover, the methods for identifying optic discs in color fundus images use some variation of a filtering or template-matching techniques based on either vessel geometry or the geometry of the optic disc itself. These approaches cannot be applied to AF images because they rely upon correlations with the dense structure of intersecting vessels at the center of the optic disc and/or a clear distinction between the optic disc and any other structures present. Unlike color images, monochromatic AF images do not usually produce visible details sufficient to distinguish the many vessels within the optic disc. In the case of template matching, which involves calculating correlations to a well demarcated circular shape, the presence of disease may result in false positives in AF images featuring AMD due to the strong similarity to the appearance of atrophy. Atrophy also often produces smooth, round, very dark and well demarcated regions in AF images. This also limits the usefulness of other methods that use of edge detection or thresholding based on intensity or image variation at the optic disc boundary or central region.